A team of Penn State engineers has created a stretchy, wearable synaptic transistor that could turn robotics and wearable devices smarter. The device developed by the team works like neurons in the brain, sending signals to some cells and inhibiting others to enhance and weaken the devices’ memories.
The research was led by Cunjiang Yu, Dorothy Quiggle Career Development Associate Professor of Engineering Science and Mechanics and associate professor of biomedical engineering and of materials science and engineering.
The research was published in Nature Electronics.
Designing the Synaptic Transistor
The team designed the synaptic transistor to be integrated in robots or wearables, and it can use artificial intelligence (AI) to optimize functions.
“Mirroring the human brain, robots and wearable devices using the synaptic transistor can use its artificial neurons to ‘learn’ and adapt their behaviors,” Yu said. “For example, if we burn our hand on a stove, it hurts, and we know to avoid touching it next time. The same results will be possible for devices that use the synaptic transistor, as artificial intelligence is able to ‘learn’ and adapt to its environment.”
Mirroring the Human Brain
Yu says that the artificial neurons in the device were designed to perform like neurons in the ventral tegmental area, which is a small segment of the human brain. Neurons first process and transmit information by releasing neurotransmitters at their synapses, which are usually located at the neural cell ends. Excitatory neurotransmitters then trigger the activity of other neurons and are associated with enhancing memories. On the other hand, inhibitory neurotransmitters reduce the activity of other neurons, meaning they are associated with weakening memories.
“Unlike all other areas of the brain, neurons in the ventral tegmental area are capable of releasing both excitatory and inhibitory neurotransmitters at the same time,” Yu said. “By designing the synaptic transistor to operate with both synaptic behaviors simultaneously, fewer transistors are needed compared to conventional integrated electronics technology, which simplifies the system architecture and allows the device to conserve energy.”
The researchers wanted to model soft, stretchy biological tissues, so they relied on stretchable bilayer semiconductor materials to fabricate the device. This enabled it to stretch and twist while in use. But the conventional transistors were too rigid and would break when deformed.”
“The transistor is mechanically deformable and functionally reconfigurable, yet still retains its functions when stretched extensively.” Yu said. “It can attach to a robot or wearable device to serve as their outermost skin.”
- Neural Networks Learn Better by Mimicking Human Sleep Patterns
- 7 “Best” AI Translation Software & Tools (November 2022)
- Conversational AI Is Making Customers and Employees Happier. Here’s How.
- Electricity Helps Find Materials That Can “Learn”
- Lack of Trustworthy AI Can Stunt Innovation and Business Value